Opto-Electronic Engineering, Volume. 51, Issue 11, 240220-1(2024)

A solar cell defect detection model optimized and improved based on YOLOv8

Ziran Peng1...2,*, Siyuan Wang1,2, and Shenping Xiao12 |Show fewer author(s)
Author Affiliations
  • 1School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou, Hunan 412007, China
  • 2Hunan Key Laboratory of Electric Drive Control and Intelligent Equipment, Zhuzhou, Hunan 412007, China
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    References(24)

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    [2] Y T Shi, F Dai, C M Yang. Defect detection of solar photovoltaic cell. J Electron Meas Instrum, 34, 157-164(2020).

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    [4] X Chen, T Karin, A Jain. Automated defect identification in electroluminescence images of solar modules. Solar Energy, 242, 20-29(2022).

    [5] Z R Peng, Y Q Zhang, S P Xiao. Research on surface defect detection of solar cell with improved YOLOv5 algorithm. Acta Energ Sol Sin, 45, 368-375(2024).

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    [13] S Lu, K X Wu, J X Chen. Solar cell surface defect detection based on optimized YOLOv5. IEEE Access, 11, 71026-71036(2023).

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    [20] R M Zhang, Y F Xiao, Z N Jia et al. Improved YOLOv7 algorithm for target detection in complex environments from UAV perspective. Opto-Electron Eng, 51, 240051(2024).

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    Ziran Peng, Siyuan Wang, Shenping Xiao. A solar cell defect detection model optimized and improved based on YOLOv8[J]. Opto-Electronic Engineering, 2024, 51(11): 240220-1

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    Paper Information

    Category: Article

    Received: Sep. 16, 2024

    Accepted: Nov. 4, 2024

    Published Online: Jan. 24, 2025

    The Author Email: Peng Ziran (彭自然)

    DOI:10.12086/oee.2024.240220

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